A system for controlling an operation of a machine including a plurality of actuators assisting one or multiple tools to perform one or multiple tasks, in response to receiving an acoustic mixture of signals generated by the tool performing a task and by the plurality of actuators actuating the tool, submit the acoustic mixture of signals into a neural network trained to separate from the acoustic mixture a signal generated by the tool performing the task from signals generated by the actuators actuating the tool to extract the signal generated by the tool performing the task from the acoustic mixture of signals, analyze the extracted signal to produce a state of performance of the task, and execute a control action selected according to the state of performance of the task.

A diagnostic system includes a tool to perform machining on a workpiece, a test piece to be subjected to test machining by the tool for abnormal detection, a sensor to generate sensor data representing a physical quantity generated in the test machining, and circuitry. The test piece is different from the workpiece. The circuitry controls the tool to perform the test machining in each cycle of machining on the workpiece and calculates a degree of abnormality from the sensor data of the test machining. The test machining is performed on the test piece under a test machining condition corresponding to a machining condition of the machining on the workpiece.

A system for controlling an operation of a machine including a plurality of actuators assisting one or multiple tools to perform one or multiple tasks, in response to receiving an acoustic mixture of signals generated by the tool performing a task and by the plurality of actuators actuating the tool, submit the acoustic mixture of signals into a neural network trained to separate from the acoustic mixture a signal generated by the tool performing the task from signals generated by the actuators actuating the tool to extract the signal generated by the tool performing the task from the acoustic mixture of signals, analyze the extracted signal to produce a state of performance of the task, and execute a control action selected according to the state of performance of the task.

The present disclosure is directed toward a method for monitoring health of a machining tool operable in a machining state to form a workpiece and a non-machining state. The method includes determining whether a machine health routine is to be performed based on a machine health record stored by the control system, and retrieving a non-machining cyclic schedule, in response to the machine health routine having to be performed, where the non-machining cyclic schedule defines a timetable for performing one or more maintenance routines. The method further includes identifying a primary maintenance routine from among the one or more maintenance routines based on the non-machining cyclic schedule, and scheduling the machine health routine with the primary maintenance routine.

The present disclosure is directed toward a method for monitoring health of a machining tool operable in a machining state to form a workpiece and a non-machining state. The method includes determining whether a machine health routine is to be performed based on a machine health record stored by the control system, and retrieving a non-machining cyclic schedule, in response to the machine health routine having to be performed, where the non-machining cyclic schedule defines a timetable for performing one or more maintenance routines. The method further includes identifying a primary maintenance routine from among the one or more maintenance routines based on the non-machining cyclic schedule, and scheduling the machine health routine with the primary maintenance routine.